ArticleScientific reports2022
Predicting health-related social needs in Medicaid and Medicare populations using machine learning.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Artificial Intelligence and Machine Learning for Identifying Social Determinants of Health in Low-Income Populations Within United States Health Systems: A Scoping Review.Health science reports · 2026Article
- SDOH Data as Health Care Data: The Multifaceted, Evolving, and Consequential Role of Law and Policy.Advances in health information science and practice · 2026Review
- Performance of 2-stage health-related social needs screening using area-level measures.The American journal of managed care · 2025Article
- Integrating a risk prediction score in a clinical decision support to identify patients with health-related social needs in the emergency department.JAMIA open · 2025Article
- Performance of 4 Methods to Assess Health-Related Social Needs.JAMA network open · 2025Article
- The complexity of pharmaceutical expenditures across U.S. states.Scientific reports · 2025Article
- Predicting Health-Related Quality of Life Using Social Determinants of Health: A Machine Learning Approach with the All of Us Cohort.Bioengineering (Basel, Switzerland) · 2025Article
- Development and validation of computable social phenotypes for health-related social needs.JAMIA open · 2025Article
- Identifying Veterans with a Higher Risk of Social Needs Using Cluster Analysis.Journal of general internal medicine · 2025Article
- Social Risks and Nonadherence to Recommended Cancer Screening Among US Adults.JAMA network open · 2025Article
- Article
- The role of a social determinants of health summary measure on the association between cancer history status and colorectal cancer screening utilization among screening eligible adults.Preventive medicine reports · 2024Article
- Development of a Social Risk Score in the Electronic Health Record to Identify Social Needs Among Underserved Populations: Retrospective Study.JMIR formative research · 2024Article
- Toward standardization, harmonization, and integration of social determinants of health data: A Texas Clinical and Translational Science Award institutions collaboration.Journal of clinical and translational science · 2024Article
- Article
- Understanding individual health-related social needs in the context of area-level social determinants of health: The case for granularity.Journal of clinical and translational science · 2024Article
- Predicting Hospitalization among Medicaid Home- and Community-Based Services Users Using Machine Learning Methods.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2023Article
- Toward informatics-enabled preparedness for natural hazards to minimize health impacts of climate change.Journal of the American Medical Informatics Association : JAMIA · 2022Review
- Individual-Level and Neighborhood-Level Factors Associated with Longitudinal Changes in Cardiometabolic Measures in Participants of a Clinic-Based Care Coordination Program: A Secondary Data Analysis.Journal of clinical medicine · 2022Article
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Authors and funding
6 authors.
Funding
Abstract
Providers currently rely on universal screening to identify health-related social needs (HRSNs). Predicting HRSNs using EHR and community-level data could be more efficient and less resource intensive. Using machine learning models, we evaluated the predictive performance of HRSN status from EHR and community-level social determinants of health (SDOH) data for Medicare and Medicaid beneficiaries participating in the Accountable Health Communities Model. We hypothesized that Medicaid insurance coverage would predict HRSN status. All models significantly outperformed the baseline Medicaid hypothesis. AUCs ranged from 0.59 to 0.68. The top performance (AUC = 0.68 CI 0.66-0.70) was achieved by the "any HRSNs" outcome, which is the most useful for screening prioritization. Community-level SDOH features had lower predictive performance than EHR features. Machine learning models can be used to prioritize patients for screening. However, screening only patients identified by our current model(s) would miss many patients. Future studies are warranted to optimize prediction of HRSNs.
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